Abstract The properties of materials and structures typically remain fixed after being designed and manufactured. There is a growing interest in systems with the capability of altering their behaviors without changing geometries or material constitutions, because such reprogrammable behaviors could unlock multiple functionalities within a single design. We introduce an optimization-driven approach, based on multi-objective magneto-mechanical topology optimization, to design magneto-active metamaterials and structures whose properties can be seamlessly reprogrammed by switching on and off the external stimuli fields. This optimized material system exhibits one response under pure mechanical loading, and switches to a distinct response under joint mechanical and magnetic stimuli. We discover and experimentally demonstrate magneto-mechanical metamaterials and metastructures that realize a wide range of reprogrammable responses, including multi-functional actuation responses, adaptable snap-buckling behaviors, switchable deformation modes, and tunable bistability. The proposed approach paves the way for promising applications such as magnetic actuators, soft robots, and energy harvesters.
Digital synthesis of free-form multimaterial structures for realization of arbitrary programmed mechanical responses
Programming structures to realize any prescribed mechanical response under large deformation is highly desired for various functionalities, such as actuation and energy trapping. Yet, the use of a single material phase and heuristically developed structural patterns leads to restricted design space and potential failure to achieve specific target behaviors. Here, through a free-form inverse design approach, multiple hyperelastic materials with distinct properties are optimally synthesized into composite structures to precisely achieve arbitrary and extreme prescribed responses under large deformations. The digitally synthesized structures exhibit organic shapes and motions with irregular distributions of material phases. Within the structures, different materials play distinct roles yet seamlessly collaborate through sophisticated deformation mechanisms to produce the target behaviors, some of which are unachievable by a single material. While complex in geometry and material heterogeneity, the discovered structures are effectively manufactured via multimaterial fabrication with different polydimethylsiloxane (PDMS) elastomers with distinct behaviors and their highly nonlinear responses are physically and accurately realized in experiments. To enhance programmability, the synthesized structures are heteroassembled into architectures that exhibit highly complex yet navigable responses. The proposed synthesis, multimaterial fabrication, and heteroassembly strategy can be utilized to design function-oriented and situation-specific mechanical devices for a wide range of applications.
- Award ID(s):
- Publication Date:
- NSF-PAR ID:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Sponsoring Org:
- National Science Foundation
More Like this
We present a novel optimization framework for optimal design of structures exhibiting memory characteristics by incorporating shape memory polymers (SMPs). SMPs are a class of memory materials capable of undergoing and recovering applied deformations. A finite-element analysis incorporating the additive decomposition of small strain is implemented to analyze and predict temperature-dependent memory characteristics of SMPs. The finite element method consists of a viscoelastic material modelling combined with a temperature-dependent strain storage mechanism, giving SMPs their characteristic property. The thermo-mechanical characteristics of SMPs are exploited to actuate structural deflection to enable morphing toward a target shape. A time-dependent adjoint sensitivity formulation implemented through a recursive algorithm is used to calculate the gradients required for the topology optimization algorithm. Multimaterial topology optimization combined with the thermo-mechanical programming cycle is used to optimally distribute the active and passive SMP materials within the design domain. This allows us to tailor the response of the structures to design them with specific target displacements, by exploiting the difference in the glass-transition temperatures of the two SMP materials. Forward analysis and sensitivity calculations are combined in a PETSc-based optimization framework to enable efficient multi-functional, multimaterial structural design with controlled deformations.
Magnetic actuation has emerged as a powerful and versatile mechanism for diverse applications, ranging from soft robotics, biomedical devices to functional metamaterials. This highly interdisciplinary research calls for an easy to use and efficient modeling/simulation platform that can be leveraged by researchers with different backgrounds. Here we present a lattice model for hard-magnetic soft materials by partitioning the elastic deformation energy into lattice stretching and volumetric change, so-called ‘magttice’. Magnetic actuation is realized through prescribed nodal forces in magttice. We further implement the model into the framework of a large-scale atomic/molecular massively parallel simulator (LAMMPS) for highly efficient parallel simulations. The magttice is first validated by examining the deformation of ferromagnetic beam structures, and then applied to various smart structures, such as origami plates and magnetic robots. After investigating the static deformation and dynamic motion of a soft robot, the swimming of the magnetic robot in water, like jellyfish's locomotion, is further studied by coupling the magttice and lattice Boltzmann method (LBM). These examples indicate that the proposed magttice model can enable more efficient mechanical modeling and simulation for the rational design of magnetically driven smart structures.
(Digital Presentation) Activating the Ion Transmission at the Cathode-Electrolyte Interface in All-Solid-State BatteriesAll-solid-state batteries (ASSBs) have garnered increasing attention due to the enhanced safety, featuring nonflammable solid electrolytes as well as the potential to achieve high energy density. 1 The advancement of the ASSBs is expected to provide, arguably, the most straightforward path towards practical, high-energy, and rechargeable batteries based on metallic anodes. 1 However, the sluggish ion transmission at the cathode-electrolyte (solid/solid) interface would result in the high resistant at the contact and limit the practical implementation of these all solid-state materials in real world batteries. 2 Several methods were suggested to enhance the kinetic condition of the ion migration between the cathode and the solid electrolyte (SE). 3 A composite strategy that mixes active materials and SEs for the cathode is a general way to decrease the ion transmission barrier at the cathode-electrolyte interface. 3 The active material concentration in the cathode is reduced as much as the SE portion increases by which the energy density of the ASSB is restricted. In addition, the mixing approach generally accompanies lattice mismatches between the cathode active materials and the SE, thus providing only limited improvements, which is imputed by random contacts between the cathode active materials and the SE during the mixingmore »
The coconut shell consists of three distinct layers: the skin-like outermost exocarp, the thick fibrous mesocarp, and the hard and tough inner endocarp. In this work, we focused on the endocarp because it features a unique combination of superior properties, including low weight, high strength, high hardness, and high toughness. These properties are usually mutually exclusive in synthesized composites. The microstructures of the secondary cell wall of the endocarp at the nanoscale, in which cellulose microfibrils are surrounded by hemicellulose and lignin, were generated. All-atom molecular dynamics simulations with PCFF force field were conducted to investigate the deformation and failure mechanisms under uniaxial shear and tension. Steered molecular dynamics simulations were carried out to study the interaction between different types of polymer chains. The results demonstrated that cellulose–hemicellulose and cellulose–lignin exhibit the strongest and weakest interactions, respectively. This conclusion was further validated against the DFT calculations. Additionally, through shear simulations of sandwiched polymer models, it was found that cellulose–hemicellulose-cellulose exhibits the highest strength and toughness, while cellulose–lignin-cellulose shows the lowest strength and toughness among all tested cases. This conclusion was further confirmed by uniaxial tension simulations of sandwiched polymer models. It was revealed that hydrogen bonds formed between the polymermore »